室内弱阴影环境下L~N模型参数估计及实验验证
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  • 英文篇名:The parameter estimation and experimental verification of L~N model for weak-shadow environment indoor
  • 作者:蔡傲 ; 袁洪 ; 刘博文
  • 英文作者:CAI Ao;YUAN Hong;LIU Bo-wen;School of Information Science and Engineering, Yunnan University;
  • 关键词:LN模型 ; 参数估计 ; 矩估计法 ; 统计特性 ; Lognormal模型
  • 英文关键词:LN model;;parameter estimation;;Moment-Method Estimation;;statistical properties;;Lognormal model
  • 中文刊名:YNDZ
  • 英文刊名:Journal of Yunnan University(Natural Sciences Edition)
  • 机构:云南大学信息学院;
  • 出版日期:2019-03-10
  • 出版单位:云南大学学报(自然科学版)
  • 年:2019
  • 期:v.41;No.200
  • 基金:国家自然科学基金(61561051)
  • 语种:中文;
  • 页:YNDZ201902008
  • 页数:9
  • CN:02
  • ISSN:53-1045/N
  • 分类号:47-55
摘要
针对描述弱阴影信道的L~N模型未对模型进行参数估计及实用性验证的问题,对该模型进行参数估计,最后验证模型的准确性和灵活性.首先利用矩估计法估计该模型的参数,并在室内弱阴影散射多径环境下进行体域网实验测量得到原始数据,然后用滑动窗口法从原始数据分离出能够被L~N模型描述的弱阴影衰落测试数据,再利用测试数据计算模型的待估计参数,最后用Matlab计算该模型的统计特性的理论与仿真模型结果,与测试数据计算得到的统计特性进行对比,验证该模型的准确性;通过仿真比较具有相同均值和方差的Lognormal模型和L~N模型(N取不同值)的理论统计特性,验证该模型的灵活性.
        Aiming at the problem that nobody estimated the statistical parameters, and verified the practicability of L~N model that describe weak-shadow channel, we estimate parameters of the model and verify the accuracy and flexibility of the model.Firstly, we use the Moment-Method Estimation to estimate the parameters of the model, and the body-area network experimental measurement is performed in a weak-shadow and multipathscatter environment indoor to obtain the original data, and use the sliding window method to separate the test data of weak-shadow fading that can be discribed by L~N model from the original data, and use the test data to calculate the parameters of the model. Then we use the matlab to calculate the statistical characteristics of theory and simulation model of the L~N model, and compare with the statistical characteristics calculated by the test data to verified the accuracy of the model. Finally, we compare the theoretical statistical characteristics of Lognormal model and LN model(with different N values) with the same mean and variance by simulation to verify the flexibility of the model.
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